Zaloguj się
Deutsch English Español Polski
Średnia

Segfault in `tf.raw_ops.TensorListConcat`

  • Ujawniono: 21.11.2022
  • Aktualizacja: 11.10.2026 14:18

Impact

If tf.raw_ops.TensorListConcat is given element_shape=[], it results segmentation fault which can be used to trigger a denial of service attack.

python
import tensorflow as tf
tf.raw_ops.TensorListConcat(
    input_handle=tf.data.experimental.to_variant(tf.data.Dataset.from_tensor_slices([1, 2, 3])),
    element_dtype=tf.dtypes.float32,
    element_shape=[]
)

Patches

We have patched the issue in GitHub commit fc33f3dc4c14051a83eec6535b608abe1d355fde.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Tong Liu, ShanghaiTech University

Czego dotyczy

Kliknij technologię, aby zobaczyć wszystkie dotyczące jej podatności.

PlatformaPaczkaPodatne wersjePoprawka w wersji
Python (PyPI) tensorflow < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
Python (PyPI) tensorflow-cpu < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
Python (PyPI) tensorflow-gpu < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1

Odnośniki

Ocena CVSS 4.8/10
Wektor CVSS
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Słabość (CWE)
CWE-20
Platforma
Python (PyPI)
Paczka
tensorflow, tensorflow-cpu, tensorflow-gpu
Ujawniono
21.11.2022
Aktualizacja
11.10.2026 14:18

Źródła i licencje

OSV / GitHub Advisory Database - PYSEC-2026-3117 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2026-3283 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-66vq-54fq-6jvv - CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2026-957 - PyPA Advisory Database; CC BY 4.0

Historia podatności: tensorflow

Wszystkie opisane podatności tej paczki (Python (PyPI)), od najnowszej. Widać, czy to jednorazowa wpadka, czy paczka, której trzeba pilnować.

Wszystkie (433) w archiwum
Wszystkich wpisów
433
Pierwsza → ostatnia
04.2019 07.2024
Bez poprawki
0
Wykorzystywana w atakach
0

Rozkład istotności

  • Krytyczna 6
  • Wysoka 112
  • Średnia 210
  • Niska 105

Ujawnienia w latach

Istotność:
  1. TensorFlow has segfault in array_ops.upper_bound
    Wysoka · 7.5 CVE-2023-33976 < 2.12.1 2.12.1
  2. TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
    Wysoka · 7.5 CVE-2023-25659 < 2.11.1 2.11.1
  3. TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
    Wysoka · 7.5 CVE-2023-25660 < 2.11.1 2.11.1
  4. TensorFlow vulnerable to integer overflow in EditDistance
    Wysoka · 7.5 CVE-2023-25662 < 2.11.1 2.11.1
  5. TensorFlow has Null Pointer Error in TensorArrayConcatV2
    Wysoka · 7.5 CVE-2023-25663 < 2.11.1 2.11.1
  6. TensorFlow has Heap-buffer-overflow in AvgPoolGrad
    Wysoka · 7.5 CVE-2023-25664 < 2.11.1 2.11.1
  7. TensorFlow has Null Pointer Error in SparseSparseMaximum
    Wysoka · 7.5 CVE-2023-25665 < 2.11.1 2.11.1
  8. TensorFlow has Floating Point Exception in AudioSpectrogram
    Wysoka · 7.5 CVE-2023-25666 < 2.11.1 2.11.1
  9. TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation
    Krytyczna · 9.8 CVE-2023-25668 < 2.11.1 2.11.1
  10. TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
    Wysoka · 7.5 CVE-2023-25669 < 2.11.1 2.11.1
  11. TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
    Wysoka · 7.5 CVE-2023-25670 < 2.11.1 2.11.1
  12. TensorFlow has segmentation fault in tfg-translate
    Wysoka · 7.5 CVE-2023-25671 < 2.11.1 2.11.1
  13. TensorFlow has Null Pointer Error in LookupTableImportV2
    Wysoka · 7.5 CVE-2023-25672 < 2.11.1 2.11.1
  14. TensorFlow has Floating Point Exception in TensorListSplit with XLA
    Wysoka · 7.5 CVE-2023-25673 < 2.11.1 2.11.1
  15. TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
    Wysoka · 7.5 CVE-2023-25674 < 2.11.1 2.11.1
  16. TensorFlow has Segfault in Bincount with XLA
    Wysoka · 7.5 CVE-2023-25675 < 2.11.1 2.11.1
  17. TensorFlow has null dereference on ParallelConcat with XLA
    Wysoka · 7.5 CVE-2023-25676 < 2.11.1 2.11.1
  18. TensorFlow has double free in Fractional(Max/Avg)Pool
    Wysoka · 8.0 CVE-2023-25801 < 2.11.1 2.11.1
  19. TensorFlow has Floating Point Exception in TFLite in conv kernel
    Wysoka · 7.5 CVE-2023-27579 < 2.11.1 2.11.1
  20. TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad
    Wysoka · 7.5 CVE-2023-25658 < 2.11.1 2.11.1
  21. Out of bounds write in grappler in Tensorflow
    Wysoka · 7.1 CVE-2022-41902 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  22. FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess
    Wysoka · 7.1 CVE-2022-41900 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  23. Buffer overflow in `CONV_3D_TRANSPOSE` on TFLite
    Wysoka · 7.1 CVE-2022-41894 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  24. Segfault in `tf.raw_ops.TensorListConcat` ten wpis
    Średnia · 4.8 CVE-2022-41891 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  25. TensorFlow vulnerable to OOB write in `scatter_nd` in TF Lite
    Wysoka · 7.0 CVE-2022-35939 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  26. TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite
    Wysoka · 7.0 CVE-2022-35937 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  27. Code injection in `saved_model_cli` in TensorFlow
    Wysoka · 7.8 CVE-2022-29216 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  28. Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow
    Wysoka · 7.1 CVE-2022-29208 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  29. NULL Pointer Dereference and Access of Uninitialized Pointer in TensorFlow
    Krytyczna · 9.3 ghsa-h6gw-r52c-724r < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  30. Improper Validation of Integrity Check Value in TensorFlow
    Wysoka · 7.0 ghsa-43q8-3fv7-pr5x < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  31. Out of bounds read in Tensorflow
    Wysoka · 8.8 CVE-2022-23594 >= 2.7.0, < 2.7.1 2.7.1
  32. Read and Write outside of bounds in TensorFlow
    Wysoka · 8.8 CVE-2022-23560 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  33. Insecure temporary file in Tensorflow
    Wysoka · 7.1 CVE-2022-23563 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  34. Out of bounds read in Tensorflow
    Wysoka · 8.1 CVE-2022-23592 >= 2.8.0-rc0, < 2.8.0 2.8.0
  35. Stack overflow in TensorFlow
    Wysoka · 7.5 CVE-2022-23591 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  36. Out of bounds read and write in Tensorflow
    Wysoka · 8.8 CVE-2022-23574 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  37. Uninitialized variable access in Tensorflow
    Wysoka · 7.6 CVE-2022-23573 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  38. Integer overflow in Tensorflow
    Wysoka · 7.6 CVE-2022-23562 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  39. Out of bounds write in TFLite
    Wysoka · 8.8 CVE-2022-23561 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  40. Integer overflow in TFLite
    Wysoka · 8.8 CVE-2022-23559 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  41. Out of bounds write in Tensorflow
    Wysoka · 8.8 CVE-2022-23566 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  42. Use after free in `DecodePng` kernel
    Wysoka · 7.6 CVE-2022-23584 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  43. Integer overflow in TFLite array creation
    Wysoka · 7.6 CVE-2022-23558 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  44. Integer overflow in TensorFlow
    Wysoka · 8.8 CVE-2022-23587 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  45. Heap overflow in Tensorflow
    Wysoka · 7.6 CVE-2022-21740 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  46. Division by zero in TFLite
    Wysoka · 6.5 CVE-2022-21741 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  47. Null pointer dereference in TensorFlow
    Wysoka · 6.5 CVE-2022-21739 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  48. Assertion failure based denial of service in Tensorflow
    Wysoka · 6.5 CVE-2022-21737 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  49. Integer overflow leading to crash in Tensorflow
    Wysoka · 6.5 CVE-2022-21738 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  50. `CHECK`-fails when building invalid tensor shapes in Tensorflow
    Wysoka · 6.5 CVE-2022-23569 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  51. Overflow and uncaught divide by zero in Tensorflow
    Wysoka · 6.5 CVE-2022-21729 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  52. `CHECK`-failures in Tensorflow
    Wysoka · 6.5 CVE-2022-21734 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  53. Division by zero in Tensorflow
    Wysoka · 6.5 CVE-2022-21735 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  54. Undefined behavior in `SparseTensorSliceDataset`
    Wysoka · 7.6 CVE-2022-21736 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  55. Type confusion leading to segfault in Tensorflow
    Wysoka · 6.5 CVE-2022-21731 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  56. Integer overflows in Tensorflow
    Wysoka · 6.5 CVE-2022-23567 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  57. Integer overflows in Tensorflow
    Wysoka · 6.5 CVE-2022-23568 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  58. Out of bounds read in Tensorflow
    Wysoka · 8.1 CVE-2022-21726 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  59. Out of bounds read in Tensorflow
    Wysoka · 8.1 CVE-2022-21728 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  60. Integer overflow in Tensorflow
    Wysoka · 7.6 CVE-2022-21727 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  61. Out of bounds read in Tensorflow
    Wysoka · 8.1 CVE-2022-21730 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  62. Access to invalid memory during shape inference in `Cudnn*` ops
    Wysoka · 7.8 CVE-2021-41221 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  63. Use after free / memory leak in `CollectiveReduceV2`
    Wysoka · 7.8 CVE-2021-41220 >= 2.6.0, < 2.6.1 2.6.1
  64. Incomplete validation in boosted trees code
    Krytyczna · 9.3 CVE-2021-41208 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  65. Incomplete validation of shapes in multiple TF ops
    Wysoka · 7.0 CVE-2021-41206 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  66. Undefined behavior via `nullptr` reference binding in sparse matrix multiplication
    Wysoka · 7.8 CVE-2021-41219 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  67. Reference binding to `nullptr` in `tf.ragged.cross`
    Wysoka · 7.8 CVE-2021-41214 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  68. Heap OOB read in `tf.ragged.cross`
    Wysoka · 7.1 CVE-2021-41212 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  69. Heap OOB in shape inference for `QuantizeV2`
    Wysoka · 7.1 CVE-2021-41211 >= 2.6.0, < 2.6.1 2.6.1
  70. Missing validation during checkpoint loading
    Wysoka · 7.8 CVE-2021-41203 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  71. Heap OOB read in `tf.raw_ops.SparseCountSparseOutput`
    Wysoka · 7.1 CVE-2021-41210 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  72. Unitialized access in `EinsumHelper::ParseEquation`
    Wysoka · 7.8 CVE-2021-41201 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  73. Heap OOB in nested `tf.map_fn` with `RaggedTensor`s
    Wysoka · 7.1 CVE-2021-37679 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  74. Arbitrary code execution due to YAML deserialization
    Wysoka · 9.3 CVE-2021-37678 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  75. Incomplete validation in MKL requantization
    Wysoka · 7.8 CVE-2021-37665 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  76. Incomplete validation in `QuantizeV2`
    Wysoka · 7.8 CVE-2021-37663 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  77. Null pointer dereference in TFLite MLIR optimizations
    Wysoka · 7.8 CVE-2021-37689 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  78. Null pointer dereference in TFLite
    Wysoka · 7.8 CVE-2021-37688 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  79. NPE in TFLite
    Wysoka · 7.8 CVE-2021-37681 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  80. Reference binding to nullptr in shape inference
    Wysoka · 7.8 CVE-2021-37676 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  81. Reference binding to nullptr in map operations
    Wysoka · 7.8 CVE-2021-37671 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  82. Reference binding to nullptr in unicode encoding
    Wysoka · 7.8 CVE-2021-37667 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  83. Reference binding to nullptr in `RaggedTensorToVariant`
    Wysoka · 7.8 CVE-2021-37666 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  84. Use after free in boosted trees creation
    Wysoka · 7.8 CVE-2021-37652 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  85. Incorrect validation of `SaveV2` inputs
    Wysoka · 7.8 CVE-2021-37648 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  86. Heap OOB in boosted trees
    Wysoka · 7.3 CVE-2021-37664 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  87. Reference binding to nullptr and heap OOB in binary cwise ops
    Wysoka · 7.3 CVE-2021-37659 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  88. Heap OOB in `ResourceScatterUpdate`
    Wysoka · 7.3 CVE-2021-37655 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  89. Heap OOB and CHECK fail in `ResourceGather`
    Wysoka · 7.3 CVE-2021-37654 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  90. Heap buffer overflow in `FractionalAvgPoolGrad`
    Wysoka · 7.1 CVE-2021-37651 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  91. Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord`
    Wysoka · 7.8 CVE-2021-37650 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  92. Heap out of bounds access in sparse reduction operations
    Wysoka · 7.3 CVE-2021-37635 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  93. Null pointer dereference in `UncompressElement`
    Wysoka · 7.7 CVE-2021-37649 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  94. Null pointer dereference in `SparseTensorSliceDataset`
    Wysoka · 7.7 CVE-2021-37647 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  95. Null pointer dereference in `MatrixDiagPartOp`
    Wysoka · 7.7 CVE-2021-37643 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  96. Null pointer dereference and heap OOB read in operations restoring tensors
    Wysoka · 8.4 CVE-2021-37639 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  97. Null pointer dereference in `RaggedTensorToTensor`
    Wysoka · 7.7 CVE-2021-37638 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  98. Null pointer dereference in `CompressElement`
    Wysoka · 7.7 CVE-2021-37637 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  99. Stack overflow due to looping TFLite subgraph
    Wysoka · 7.3 CVE-2021-29591 < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 2.1.4, 2.2.3, 2.3.3, 2.4.2
  100. TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
    Wysoka · 9.1 CVE-2020-26269 >= 2.4.0rc0, < 2.4.0 2.4.0
  101. Segfault in `tf.quantization.quantize_and_dequantize`
    Wysoka · 5.9 CVE-2020-15265 < 2.4.0 2.4.0
  102. Out of bounds write in tensorflow-lite
    Krytyczna · 8.1 CVE-2020-15214 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
  103. Out of bounds access in tensorflow-lite
    Krytyczna · 8.1 CVE-2020-15212 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
  104. Segmentation fault in tensorflow-lite
    Wysoka · 6.5 CVE-2020-15210 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  105. Null pointer dereference in tensorflow-lite
    Wysoka · 5.9 CVE-2020-15209 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  106. Data corruption in tensorflow-lite
    Wysoka · 7.4 CVE-2020-15208 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  107. Denial of Service in Tensorflow
    Wysoka · 9.0 CVE-2020-15206 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  108. Denial of Service in Tensorflow
    Wysoka · 7.5 CVE-2020-15203 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  109. Integer truncation in Shard API usage
    Wysoka · 9.0 CVE-2020-15202 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  110. Segfault in Tensorflow
    Wysoka · 5.9 CVE-2020-15200 >= 2.3.0, < 2.3.1 2.3.1
  111. Denial of Service in Tensorflow
    Wysoka · 5.9 CVE-2020-15199 >= 2.3.0, < 2.3.1 2.3.1
  112. Memory corruption in Tensorflow
    Wysoka · 7.1 CVE-2020-15193 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
  113. TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decode
    Wysoka · 6.5 CVE-2018-21233 < 1.7.0 1.7.0
  114. Google TensorFlow 1.7.x and earlier is affected by a Buffer Overflow vulnerability. The type of exploitation is context-dependent.
    Krytyczna · 9.8 CVE-2018-7575 >= 1.0.0, < 1.7.1 1.7.1
  115. NULL pointer dereference in Google TensorFlow before 1.12.2 could cause a denial of service via an invalid GIF file.
    Wysoka · 6.5 CVE-2019-9635 >= 1.0.0, < 1.12.1 1.12.1
  116. Memcpy parameter overlap in Google Snappy library 1.1.4, as used in Google TensorFlow before 1.7.1, could result in a crash or read from other parts of process memory.
    Wysoka · 8.1 CVE-2018-7577 >= 1.1.0, < 1.7.1 1.7.1
  117. Invalid memory access and/or a heap buffer overflow in the TensorFlow XLA compiler in Google TensorFlow before 1.7.1 could cause a crash or read from other parts of process memory via a crafted config
    Wysoka · 8.1 CVE-2018-10055 >= 1.1.0, < 1.7.1 1.7.1
  118. Google TensorFlow 1.7 and below is affected by: Buffer Overflow. The impact is: execute arbitrary code (local).
    Wysoka · 8.8 CVE-2018-8825 >= 1.5.0, < 1.7.1 1.7.1
  119. Google TensorFlow 1.6.x and earlier is affected by: Null Pointer Dereference. The type of exploitation is: context-dependent.
    Wysoka · 6.5 CVE-2018-7576 >= 1.0.0, < 1.6.0 1.6.0

Dowiedz się, które podatności dotyczą Twojej aplikacji

Po podłączeniu integracji DockRay i włączeniu raportowania oprogramowania DockRay porównuje zgłoszone wersje komponentów ze znanymi podatnościami i powiadamia o potwierdzonych dopasowaniach. Zakres zależy od obsługiwanej technologii i dostępnych biuletynów.

Podłącz swoją aplikację
Newsletter DockRay

Bezpieczeństwo aplikacji w Twojej skrzynce

Najważniejsze podatności, konkretne zalecenia i praktyczne wskazówki dla Twoich aplikacji. Wybierz technologie i śledź to, co ma znaczenie dla Twojego projektu.

  • Codzienne zestawienie nowych podatności, także krytycznych.
  • Powiadomienia o ważnych aktualizacjach.
  • Praktyczne porady o bezpieczeństwie i monitoringu aplikacji.

Pozostaw puste, aby otrzymywać informacje o wszystkich technologiach.

Polityka prywatności

Zapis jest bezpłatny. Wypiszesz się jednym kliknięciem w wiadomości.